On the presentation of the necessary conditions for satisfiability of the premises of the JSM-induction rules for analyzing medical data

This paper formulates the necessary and necessary and sufficient conditions for satisfiability of the premises of the inductive inference rules in intelligent systems for analyzing medical data.     

Learning a decision maker's utility function from (possibly) inconsistent behavior

When modeling a decision problem using the influence diagram framework, the quantitative part rests on two principal components: probabilities for representing the decision maker's uncertainty about the domain and utilities for representing preferences. Over the last decade, several methods have been developed for learning the probabilities from a database. However, methods for learning the utilities have only received limited attention in the computer science community.

A promising approach for learning a decision maker's utility function is to take outset in the decision maker's observed behavioral patterns, and then find a utility function which (together with a domain model) can explain this behavior. That is, it is assumed that decision maker's preferences are reflected in the behavior. Standard learning algorithms also assume that the decision maker is behavioral consistent, i.e., given a model of the decision problem, there exists a utility function which can account for all the observed behavior. Unfortunately, this assumption is rarely valid in real-world decision problems, and in these situations existing learning methods may only identify a trivial utility function. In this paper we relax this consistency assumption, and propose two algorithms for learning a decision maker's utility function from possibly inconsistent behavior; inconsistent behavior is interpreted as random deviations from an underlying (true) utility function. The main difference between the two algorithms is that the first facilitates a form of batch learning whereas the second focuses on adaptation and is particularly well-suited for scenarios where the DM's preferences change over time. Empirical results demonstrate the tractability of the algorithms, and they also show that the algorithms converge toward the true utility function for even very small sets of observations.     

Blue-Green (~480 nm) versus Blue (~460 nm) Light for Newborn Phototherapy—Safety Considerations

We have previously shown that the phototherapy of hyperbilirubinemic neonates using blue-green LED light with a peak wavelength of ~478 nm is 31% more efficient for removing unconjugated bilirubin from circulation than blue LED light with a peak wavelength of ~452 nm. Based on these results, we recommended that the phototherapy of hyperbilirubinemic newborns be practiced with light of ~480 nm. Aim: Identify and discuss the most prominent potential changes that have been observed in the health effects of phototherapy using either blue fluorescent- or blue LED light and speculate on the expected effects of changing to blue-green LED light phototherapy. Search the phototherapy literature using the terms neonate, hyperbilirubinemia, and phototherapy in the PubMed and Embase databases. Transitioning from blue fluorescent light to blue-green LED light will expose neonates to less light in the 400–450 nm spectral range, potentially leading to less photo-oxidation and geno-/cytotoxicity, reduced risk of cancer, and decreased mortality in extremely low-birthweight neonates. The riboflavin level may decline, and the increased production and retention of bronze pigments may occur in predisposed neonates due to enhanced lumirubin formation. The production of pre-inflammatory cytokines may rise. Hemodynamic responses and transepidermal water loss are less likely to occur. The risk of hyperthermia may decrease with the use of blue-green LED light and the risk of hypothermia may increase. Parent–neonate attachment and breastfeeding will be positively affected because of the shortened duration of phototherapy. The latter may also lead to a significant reduction in the cost of phototherapy procedures as well as the hospitalization process.     

An improved method for preparing monolithic aerogels based on methyltrimethoxysilane at ambient pressure Part II: Microstructure and performance of the aerogels

The microstructures, physical properties and mechanical properties of the methyltrimethoxysilane (MTMS) derived aerogels, prepared at ambient pressure using an improved method reported in Part I, have been comprehensively characterised in this paper, as Part II. The study has revealed sophisticated pore structures and morphologies of the aerogels produced, and demonstrated the relationships between the key processing conditions and microstructures of the resultant aerogels. The results of the study also help to further understand the effect of microstructure changes on the macrostructure, volume shrinkage and performances of the aerogels, and provide a general guide on how to manipulate the processing conditions to produce monolithic MTMS based aerogels with desirable structure and properties by ambient pressure drying.     

metaSMT: focus on your application and not on solver integration

International Journal on Software Tools for Technology Transfer - Many applications from artificial intelligence and formal methods use decision procedures as their core solving engines. In this...     

DIOS-MSEED: A chip-based method for measurement of enantiomeric excess by kinetic resolution/mass spectrometry

The determination of enantiomeric excess by kinetic resolution mass spectrometry has been implemented with the Desorption/Ionization On Silicon (DIOS) MS technique. Measurements can thereby be made much more rapidly than was previously possible, bringing this general methodology for screening asymmetric catalysts closer to true high-throughput status.     

Deformation and water loss from solvent filled microcapsules under compressive loads

Microcapsules filled with liquid solvents for CO₂ absorption can be easily deformed due to their elastic polymer shells. We present a combination of experiments and model predictions to demonstrate that modest compressive forces can lead to significant capsule deformation and performance issues for this enabling technology. Contrary to expectations based on Raoult's law, capsules containing aqueous carbonate solution were found to lose water to flows of humidified nitrogen in centimeter-scale packed beds. Water loss increased with gas velocity, suggesting compression was responsible for mass transfer, an interpretation supported by microscope images of deformed and broken capsules. A model for compression induced mass transfer under packed/fluidized bed operating conditions was developed and validated with the experimental data for a range of conditions (gas velocities, temperatures, humidities). Design criteria for future generations of microcapsules that will more effectively resist compression are evaluated.     

Light aromatics from the hydropyrolysis of coal

The hydropyrolysis of British coals was studied at hydrogen pressures of 5–15 MPa using heating rates of up to 30 K s^?1. In a single-stage reactor, hydropyrolysis of a high-volatile coal gave a maximum yield of 4.5 Wt % of single-ring aromatics. The results suggested that the evolution of volatiles and their cracking to benzene, toluene and xylenes were sequential reactions. This was confirmed using a two-stage reactor in which the coal was heated in one zone and the volatiles cracked in a separate, isothermally heated zone. Yields of up to 12 wt % benzene were then obtained from a high-volatile bituminous coal in hydrogen at 15 MPa, both the cracking temperature and the vapour residence time being separately optimized. Hydropyrolysis of model compounds showed that benzene was a major product of the cracking of polynuclear aromatics under hydrogen pressure.